Abstract
In this paper, the volatility of the return generating process of the market portfolio and the slope coefficient of the market model is assumed to follow a Markov switching process of order one. The results indicate very strong evidence of volatility switching behaviour in a sample of returns in the S&P500 index. In three of the thirty securities in the Dow Jones index, the estimated slope in the market model show strong switching behaviour. In these three securities the low risk state is more persistent than the high-risk state. For each security we estimate the conditional probabilities that the security is in the high (low) risk state given the market is in the high (low) volatility regime and show that this information can be used to classify securities into three distinct groups. There is no association between these groups and the securities' constant beta estimated in the market model and the Sharpe index. Some directions for further research are discussed.
Highlights
The beta - the percentage change in a security price relative to percentage change of a relevant market index - is one of the most commonly used measures of security priceThe authors would like to thank Heather Anderson for helpful comments
In a sample of returns of the thirty Dow Jones industrial securities and with Standard and Poor’s 500 Index (S&P500) index as a proxy for the market portfolio, we identify three distinct groups of securities: (i) the securities with high probability of being in the low risk state given the market is in the low volatility regime, (ii) the securities with high probability of being in the high risk state given the market is in the high volatility regime, and (iii) other securities
A sample of daily returns of the S&P500 index that we use as a proxy for the market portfolio reveals strong volatility switching behaviour with low-volatility regime being more persistent than the high-volatility regime
Summary
The beta - the percentage change in a security price relative to percentage change of a relevant market index - is one of the most commonly used measures of security priceThe authors would like to thank Heather Anderson for helpful comments. Two popular methods suggested in the literature to model variation in market volatility is the ARCH and GARCH processes due to Engle (1982) and Bollerslev (1986) respectively. Another approach to model financial time series is the Markov switching technique proposed by Hamilton (1989) where the parameters are viewed as the outcome of a discrete-state Markov process. Such models are known to accurately capture typical stock market patterns such as jumps and crashes. Such models are known to accurately capture typical stock market patterns such as jumps and crashes. Hamilton and Susmel (1994) modelled changes in market volatility as a Markov-switching model and as ARCH models without switching and reported evidence in favour of the former
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